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Integral imaging is a type of true three‐dimensional (3D) display technology that uses a lens array to reconstruct vivid 3D images with full parallax and true color. In order to present a high‐quality 3D image, it's vital to correct the axial position error caused by the misalignment and deformation of the lens array which makes the reconstructed lights deviate from the correct directions, resulting in severe voxel drifting and image blurring. We proposed a sub‐pixel marking method to measure the axial position error of the lenses with great accuracy by addressing the sub‐pixels under each lens and forming a homologous sub‐pixel pair. The proposed measurement method relies on the geometric center alignment of image points, which makes the measurement accuracy high. Additionally, a depth‐based sub‐pixel correction method was proposed to eliminate the voxel drifting. The proposed correction method takes the voxel depth into consideration. The experimental results well confirmed that the proposed measuring and correction methods can greatly suppress the voxel drifting caused by the axial position error of the lenses, and greatly improve the 3D image quality.

The recognition of road weather conditions can provide environmental information for autonomous driving systems, enabling them to develop safe driving strategies. Previous studies have utilized cameras or radars to identify road weather conditions, but they were unable to detect specific dry, wet, or snowy road areas. Some methods based on image segmentation can detect these areas, but their performance is limited by the similar features exhibited by dry and wet roads. In this article, we propose a novel method for segmenting dry, wet, and snowy road areas based on the fusion of images and point cloud reflection intensities. By fusing the point cloud reflection intensity, we enhance the distinction between different road types, thereby improving the accuracy of the segmentation. Furthermore, we address the challenge posed by sparser point cloud data compared to image pixels by introducing a point cloud reflection intensity upsampling method. Unlike other interpolation methods, our proposed method relies on the physical principle that an object’s reflectivity is correlated with its color and texture features, which makes the point cloud reflection intensity obtained by upsampling more reliable. To evaluate the performance of our method, we conducted experiments on a self-collected dataset that contains over 20 000 images. More than 4000 images were annotated at the pixel level, and each of them was accompanied by the corresponding point cloud data. The experimental results demonstrate that our proposed algorithm achieves an impressive mean intersection over union (mIoU) of 87.94%. Compared to image segmentation algorithms that do not fuse point clouds, our algorithm achieves an approximately 3% improvement in mIoU, substantiating its effectiveness.

Patients with systemic lupus erythematosus experience the sixth highest rate of 30‐day readmissions among chronic diseases. Timely postdischarge follow‐up is a marker of ambulatory care quality that can reduce readmissions in other chronic conditions. Our objective was to test the hypotheses that 1) beneficiaries from populations experiencing health disparities, including patients from disadvantaged neighborhoods, will have lower odds of completed follow‐up, and that 2) follow‐up will predict longer time without acute care use (readmission, observation stay, or emergency department visit) or mortality. This observational cohort study included hospitalizations in January–November 2014 from a 20% random sample of Medicare adults. Included hospitalizations had a lupus code, discharge to home without hospice, and continuous Medicare A/B coverage for 1 year before and 1 month after hospitalization. Timely follow‐up included visits with primary care or rheumatology within 30 days. Thirty‐day survival outcomes were acute care use and mortality adjusted for sociodemographic information and comorbidities. Over one‐third (35%) of lupus hospitalizations lacked 30‐day follow‐up. Younger age, living in disadvantaged neighborhoods, and rurality were associated with lower odds of follow‐up. Follow‐up was not associated with subsequent acute care or mortality in beneficiaries age <65 years. In contrast, follow‐up was associated with a 27% higher hazard for acute care use (adjusted hazard ratio [HR] 1.27 [95% confidence interval (95% CI) 1.09–1.47]) and 65% lower mortality (adjusted HR 0.35 [95% CI 0.19–0.67]) among beneficiaries age ≥65 years. One‐third of lupus hospitalizations lacked follow‐up, with significant disparities in rural and disadvantaged neighborhoods. Follow‐up was associated with increased acute care, but 65% lower mortality in older systemic lupus erythematosus patients. Further development of lupus‐specific postdischarge strategies is needed.

Stem cell-based transplantation is a promising therapeutic approach for intervertebral disc degeneration (IDD). Current limitations of stem cells include with their insufficient cell source, poor proliferation capacity, low nucleus pulposus (NP)-specific differentiation potential, and inability to avoid pyroptosis caused by the acidic IDD microenvironment after transplantation. To address these challenges, embryo-derived long-term expandable nucleus pulposus progenitor cells (NPPCs) and esterase-responsive ibuprofen nano-micelles (PEG-PIB) were prepared for synergistic transplantation. In this study, we propose a biomaterial pre-modification cell strategy; the PEG-PIB were endocytosed to pre-modify the NPPCs with adaptability in harsh IDD microenvironment through inhibiting pyroptosis. The results indicated that the PEG-PIB pre-modified NPPCs exhibited inhibition of pyroptosis in vitro; their further synergistic transplantation yielded effective functional recovery, histological regeneration, and inhibition of pyroptosis during IDD regeneration. Herein, we offer a novel biomaterial pre-modification cell strategy for synergistic transplantation with promising therapeutic effects in IDD regeneration.

In this letter, the recursive fault estimation issue is considered for nonlinear time-varying systems subject to the effects induced by energy harvesting sensors and uniform quantization. Based on the energy harvesting mechanism and stochastic distribution of the absorbed energy, the real-time occurrence probability of missing measurements is calculated recursively. This research intends to develop a recursive estimator for the considered nonlinear time-varying system with energy harvesting sensors, such that, under uniform quantization effects, the state and fault can be jointly estimated. By adopting the induction approach, an upper bound is firstly calculated for the estimation error covariances (EECs) of the state and fault. Then, the value of the time-varying estimator parameter is computed through minimizing such calculated upper bound. In the end, an illustrative example is presented to verify the availability of the developed fault estimation method.

Perovskites have attracted extensive attention as radiation detection material due to their long carrier diffusion length and lifetime, high absorption coefficient, and flexible manufacturing process. Compared with polycrystalline structures, single crystal perovskites improve the performance of optoelectronic devices due to their low defect state density, better photoelectric characteristics, and chemical stability. Herein, we review the recent progress of single crystal perovskite X-ray detectors. First, we briefly introduced the basic concepts, detection mechanisms, figure of merits of perovskite X-ray detectors, and the preparation methods of single crystal perovskites. Then, we summarized the significant advancements in single crystal perovskite X-ray detectors in recent times. Finally, we discussed the critical challenges and some practicable solutions for developing high-performance X-ray detectors.

Environment perception is one of the most critical technology of intelligent transportation systems (ITS). Motion interaction between multiple vehicles in ITS makes it important to perform multi-object tracking (MOT). However, most existing MOT algorithms follow the tracking-by-detection framework, which separates detection and tracking into two independent segments and limit the global efficiency. Recently, a few algorithms have combined feature extraction into one network; however, the tracking portion continues to rely on data association, and requires complex post-processing for life cycle management. Those methods do not combine detection and tracking efficiently. This paper presents a novel network to realize joint multi-object detection and tracking in an end-to-end manner for ITS, named as global correlation network (GCNet). Unlike most object detection methods, GCNet introduces a global correlation layer for regression of absolute size and coordinates of bounding boxes, instead of offsetting predictions. The pipeline of detection and tracking in GCNet is conceptually simple, and does not require complicated tracking strategies such as non-maximum suppression and data association. GCNet was evaluated on a multi-vehicle tracking dataset, UA-DETRAC, demonstrating promising performance compared to state-of-the-art detectors and trackers.

China is undertaking an energy reform from fossil fuels to clean energy to accomplish CO2intensity (CI) reduction commitments. After hydropower, nuclear energy is potential based on breadthwise comparison with the world and analysis of government energy consumption (EC) plan. This paper establishes a CI energy policy response forecasting model based on national and provincial EC plans. This model is then applied in Fujian Province to predict its CI from 2016 to 2020. The result shows that CI declines at a range of 43%–53% compared to that in 2005 considering five conditions of economic growth in 2020. Furthermore, Fujian will achieve the national goals in advance because EC is controlled and nuclear energy ratio increased to 16.4% (the proportion of non-fossil in primary energy is 26.7%). Finally, the development of nuclear energy in China and the world are analyzed, and several policies for energy optimization and CI reduction are proposed.

Topological quantum computation (TQC) is one of the most striking architectures that can realize fault-tolerant quantum computers. In TQC, the logical space and the quantum gates are topologically protected, i.e., robust against local disturbances. The topological protection, however, requires complicated lattice models and hard-to-manipulate dynamics; even the simplest system that can realize universal TQC—the Fibonacci anyon system—lacks a physical realization, let alone braiding the non-Abelian anyons. Here, we propose a disk model that can simulate the Fibonacci anyon system and construct the topologically protected logical spaces with the Fibonacci anyons. Via braiding the Fibonacci anyons, we can implement universal quantum gates on the logical space. Our disk model merely requires two physical qubits to realize three Fibonacci anyons at the boundary. By 15 sequential braiding operations, we construct a topologically protected Hadamard gate, which is to date the least-resource requirement for TQC. To showcase, we implement a topological Hadamard gate with two nuclear spin qubits, which reaches 97.18%fidelity by randomized benchmarking. We further prove by experiment that the logical space and Hadamard gate are topologically protected: local disturbances due to thermal fluctuations result in a global phase only. As a platform-independent proposal, our work is a proof of principle of TQC and paves the way toward fault-tolerant quantum computation.

Feshbach resonances are not restricted to small reactive systems such as F + H2and I + HI but can be found in many reactive systems. In this paper, the concept of the partial potential energy surface (PPES) is introduced. It is shown that the dynamic “Lake Eyring” explains very well the existence of reactive resonances in elementary chemical reactions. In particular, the PPESs of the Cl + CH3CH2Br and Cl + CH3CH2CH2Br systems, including the minimum energy path and the vibrational potential energy curves, were constructed using quantum chemistry methods. Based on the constructed PPESs, the scattering resonance states of these reactions could be examined and the resonance state lifetimes were estimated.

The detailed physical processes involved in slowing glacier ablation by material cover remain poorly understood so far. In the present study, using the snow cover model SNOWPACK, the effect of geotextile cover on the energy and mass balance at the tongue of the Urumqi Glacier No. 1 (Chinese Tien Shan) was simulated between July 12, 2022 and August 31, 2022. The mass changes and the energy fluxes with and without material cover were compared. The results indicated that the geotextile covering reduced glacier ablation by approximately 68% compared to the ablation in the uncovered regions. The high solar reflectivity of the geotextile reduced the net short-wave radiation energy available for the melt by 45%. Thermal insulation of the geotextile reduced the sensible heat flux by 15%. In addition, the wet geotextile exerted a cooling effect through long-wave radiation and negative latent heat flux. This cooling effect reduced the energy available for ablation by 20%. Consequently, only 37% of the energy was used for melting compared to that used in the uncovered regions (67%). Sensitivity experiments revealed that the geotextile cover used at a thickness range of 0.045–0.090 m reduced the ice loss by approximately 68%–72%, and a further increase in the thickness of the geotextile cover led to little improvements. A higher temperature and greater wind speed increased glacier ablation, although their effects were small. When the precipitation was set to zero, it led to a significantly increased melt. Overall, the geotextile effectively protected the glacier tongue from rapid melting, and the observed results have provided inspiration for developing an effective and sustainable approach to protect the glaciers using geotextile cover.

The properties of the ground and the lowest excited state of methyl bromide (CH3Br) have been studied with and without inclusion of the solvent effects in this work. The geometric parameters, energies, and frequencies of the ground state and the triplet state are calculated by using the MP2(full)/6-311++G** level of theory. The vertical excitation for the singlet state is also investigated. It is found that the theoretical results performed by the TDDFT/B3P86/6-311++G** method are in the best agreement with the experimental results. In addition, the dissociation energy of CH3Br molecule is computed at MP2(full)/6-311++G** level of theory for the gas phase and in water. The ionisation potential (IP), electron affinity (EA), electronegativity (χ), electrophilicity index (ω), hardness (η), softness (S), and chemical potential (μ) values are calculated from HOMO-LUMO energies both in the gas phase and in solvent (water). These theoretical results could serve as a guide for future experimental investigations.

In this study, we reported an improved approach for the synthesis of d/lAgrimonolide from 4‐Chlororesorcinol. It was found that a microwave assisted intramolecular esterification is an effective way to construct the 3,4‐dihydroisocoumarin core structure. The target d/lAgrimonolide is obtained in 7 steps with the overall yields of 20.7%. An improved approach for the synthesis ofd/lAgrimonolide from 4‐Chlororesorcinol is reported. It was found that microwave‐assisted intramolecular esterification is an effective way to construct the 3,4‐dihydroisocoumarin core structure. The target d/lAgrimonolide is obtained in 7 steps with the overall yield of 20.7%.

Objective To compare analgesic and mobility effects of different ropivacaine concentrations in femoral–sciatic nerve block, for postoperative analgesia in knee arthroscopy.Methods Outpatients (American Society of Anesthesiologists physical classification status of I or II), scheduled for elective knee arthroscopy, were randomly allocated to one of seven groups, prospectively investigating different concentrations of ropivacaine (0.12%; 0.14%; 0.16%; 0.18%; 0.20%; 0.22% or 0.50%), for ultrasound-guided femoral–sciatic nerve block procedures for postoperative analgesia. Visual analogue scale (VAS) pain scores and motor block evaluation scales were observed at 4, 8, 16 and 24 h postsurgery.Results In total, 105 patients were enrolled; results were analysed for 103. VAS scores for the 0.12%, 0.14% and 0.16% groups were significantly different from the 0.50% group. There were no significant differences between the 0.18%, 0.20%, 0.22% and 0.50% groups: half maximal effective concentrations and 95% maximal effective concentrations of ropivacaine were 0.158 (95% confidence intervals [CI] 0.149, 0.167) and 0.198 (95% CI 0.186, 0.221), respectively. Rates of motor blockade (Bromage score or hip motor function scale > 0) were significantly different between the 0.50% group and all other ropivacaine doses.Conclusion The 0.20% ropivacaine dose for femoral–sciatic nerve block in knee arthroscopy provided satisfactory postoperative analgesia, while preserving ability of motion.

Mesoporous and hollow structure have been attracting increasing attention for their special properties and potential applications. Here we show a facile fabrication of hollow and mesoporous ZnO microsphere via a one-step wet chemical process using polyethylene glycol (PEG, MW 200) as the solvent and soft template. The morphology and structure of the products were characterized by using scanning electron microscopy and X-ray powder diffraction techniques. Thermal analysis and Fourier transform infrared spectroscopy techniques were also performed to show the properties of the precursor and annealed product. A possible growth mechanism of hollow and mesoporous ZnO microsphere was also proposed. The Brunauer–Emmett–Teller surface area of ZnO microsphere is 28.5 m2g–1and the size of mesopores is about 10 nm. The Photoluminescence spectra of the as-synthesized ZnO hollow microspheres were also presented. The mesoporous and hollow structure enhance the gas sensitivity of ZnO microsphere, and the obtained ZnO microspheres based sensor has an excellent performance for precision detection of ethanol and acetone with low concentration.

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